Methods and apparatus to determine reach with time dependent weights

ABSTRACT

Methods and apparatus to determine reach with time dependent weights are disclosed. An example method disclosed herein includes determining a first subset of panelists exposed to media at a first time; determining a second subset of the panelists exposed to the media at a second time; applying a first plurality of weights to the first subset of panelists to generate first weighted exposures; applying a second plurality of weights to the second subset of the panelists to generate second weighted exposures; for a first panelist in the first and second subsets, determining a first cumulative weighted exposure by determining which of the first and second weighted exposures is largest for each of the first panelist; for a second panelist in one of the first and second subsets, determining a second cumulative weighted exposure by based on the weight applied to the second panelist; and determining a reach of the media for the first and second times by combining the first and second cumulative weighted exposures.

RELATED APPLICATION

This patent arises from a continuation of U.S. patent application Ser.No. 15/381,762, entitled “METHODS AND APPARATUS TO DETERMINE REACH WITHTIME DEPENDENT WEIGHTS,” and filed on Dec. 16, 2016. Priority to U.S.patent application Ser. No. 15/381,762 is claimed. U.S. patentapplication Ser. No. 15/381,762 is incorporated herein by reference inits entirety.

FIELD OF THE DISCLOSURE

This disclosure related generally to audience measurement and, moreparticularly, to methods and apparatus to determine reach with timedependent weights.

BACKGROUND

Content providers and advertisers hire panelist to yield arepresentative sample of a desired demographic group of a population ofusers. Calibrating the representative sample is a technique used toimprove estimates and reduce cost of having to construct a larger sampleto achieve the same accuracy. In some examples, calibrating therepresented sample includes weighting panelists to ensure that thepanelists accurately represent a universe of users. In this manner, whena panelist is exposed to media, the exposure is credited based on theweight of the panelist. In such examples, the weights applied to eachpanelist may vary with time as the panel and/or universe varies.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example environment in which an exampleaudience measurement entity obtains panelist data and population datafrom an example population to generate an example reach report.

FIG. 2 is a block diagram of an example implementation of an examplereach determiner of FIG. 1.

FIG. 3 is a flowchart representative of example machine readableinstructions that may be executed to implement the example reachdeterminer of FIG. 1 and/or FIG. 2.

FIG. 4 illustrates data from an example panel used to generate theexample reach report of FIG. 1.

FIG. 5 is a block diagram of an example processor platform that may beutilized to execute the example instructions of FIG. 3 to implement theexample reach determiner of FIG. 1 and/or FIG. 2.

The figures are not to scale. Wherever possible, the same referencenumbers will be used throughout the drawing(s) and accompanying writtendescription to refer to the same or like parts

DETAILED DESCRIPTION

Determining the size and specific demographics of a media viewingaudience helps media content providers and distributors schedule mediaprogramming and determine a price for advertising during theprogramming. In addition, accurate estimates of media viewingdemographics enable advertisers to target certain types and sizes ofaudiences. To collect these demographics, an audience measurementcompany enlists a plurality of media viewers (e.g., panelists) tocooperate in an audience measurement study (e.g., a panel) for apredefined length of time. The viewing habits and demographic dataassociated with the panelists are collected and used to statisticallyrepresent the total media viewing audience (e.g., a total population oruniverse). In some examples, weights are applied to each panelist suchthat the demographics of the weighted panelists match the demographicsof the total population. In some examples, the audience measuremententity determines the total audience exposed to a particular media(e.g., television programs, radio programs, movies, DVDs,advertisements, streaming media, websites, television channels, radiochannels, etc.) and/or the reach the reach of the particular media overa period of time based on the weighted panelists. As used herein, reachis a cumulative (e.g., cumulative over time) total unique audience.During a period of time when the reach may be determined, the weightsassociated with each panelist changes to adjust to a changing paneland/or universe. For example, at a first time there may be a first setof weights applied to each panelist in the panel; however, at a secondtime, additional panel members may have entered the panel changing thedynamics of the panel. As such, the audience measurement entityrecalculates the weights at the second time so that the updated panelaccurately represents the universe, thereby causing traditionalcalculation of reach (e.g., calculated based on one set of weights) tobe inaccurate. Examples disclosed herein determine the reach of mediawith time dependent weights (e.g., weights changing over the period oftime corresponding to the reach).

Examples disclosed herein generate a report identify reach over a periodof time (e.g., a cumulative period of time) while the panelists' weightsvary. The report may be based on user preferences identifying theparameters of the reach report (e.g., the media or type of media, thedifferent cumulative times to analyze, a particular subset of thepanelists to analyze, etc.). Examples disclosed herein includedetermining one or more subset of panelists that were exposed to mediaat various points in time and applying (e.g., multiplying) the varyingweights to the subset(s) at the various points in time. In this manner,weighted exposures are determined based on the varying weights. Examplesdisclosed herein further include reclusively (e.g., by looking at theweights applied at the various points in time) identifying the largestweight applied to each of the panelists based on the cumulativetime-frame of the reach report. The largest applied weights are summedto determine the reach of the media for the cumulative times. The reachcannot be more than the total universe. Accordingly, in some examples,when the reach is larger than the estimated universe total (e.g., thesum of the weights of the panelists), examples disclosed hereindetermine the reach to be estimated universe total.

An example method disclosed herein includes determining a first subsetof panelists exposed to media at a first time. The example methodfurther includes determining a second subset of the panelists exposed tothe media at the second time. The example method further includesapplying a first plurality of weights to the first subset of paneliststo generate first weighted exposures. The example method furtherincludes applying a second plurality of weights to the second subset ofpanelists to generate second weighted exposures. The example methodfurther includes a first panelist in both the first and second subsets,determining a first cumulative weighted exposure by determining which ofthe first and second weighted exposures is largest for each of the firstpanelist. The example method further includes a second panelist not inboth the first and second subsets, determining a second cumulativeweighted exposure by based on the weight applied to the second panelist.The example method further includes determining a reach of the media forthe first and second times by combining the first and second cumulativeweighted exposures.

Turning to the figures, FIG. 1 illustrates an example environment inwhich a reach with time dependent weights is determined. FIG. 1 includesan example total population 100, an example sample population 102,example panelist data 104, example population data 106, an examplenetwork 107, an example audience measurement entity (e.g., AME) 108. TheAME 108 includes an example panelist database 110, an example weighter112, an example reach determiner 114, and an example reach report 116.

The example total population 100 is a total population of users (e.g., auniverse or total audience) of a particular device or plurality ofdevices. For example, the total population 100 may be a total populationof television viewers, computing device users, mobile device users,radio listeners, Internet users, video game users, and/or any populationor combination of media users. Data, including demographic data, may beobtained and/or known for the example total population 100. The datafrom the example total population 100 is represented in the populationdata 106. The example population data 106 is transmitted to the exampleAME 108 via the example network 107. In some examples, population datamay be obtained from a database proprietor that provides service tolarge numbers of subscribers. Such service may include, but is notlimited to, cable television services, email services, social networkingservices, news media services, cloud storage services, streaming musicservices, streaming video services, satellite radio services, cellularservices, video gaming services, online retail shopping services, creditmonitoring services, etc. In some examples, the database proprietormaintains user account records corresponding to users registered for themedia services provided by the database proprietors. The user accountrecords may include demographic information (e.g., gender, age, income,location, education level, occupation, etc.). In some examples, however,media usage data may not be known for the total population 100.Alternatively, media usage data may not be released to the example AME108. Additionally or alternatively, the population data 106 may comefrom any source (e.g., surveys, queries, etc.).

In order to determine the media usage behavior and/or complexdemographics of the example total population 100, the example samplepopulation 102 may be used. The example sample population 102 is a group(e.g., a panel) of monitored panelist within the total population 100.Data from the panelist may be acquired using local people meters,portable people meters, surveys, cookies, and/or any other means forobtaining data from a panelist. The data, including media usage data anddetailed demographic data, of the example sample population 102 arerepresented in the example panelist data 104. The example panelist data104 is transmitted via the example network 107 to the example AME 108 tobe stored and calibrated (e.g., by applying weights) to represent thetotal population 100.

The example network 107 of FIG. 1 is a communications network. Theexample network 107 allows the example panelist data 104 and/or theexample population data 106 to be accessed by the example the exampleAME 108. The example network 107 may be a local area network, a widearea network, the Internet, a cloud, or any other type of communicationsnetwork.

In the illustrated example, the AME 108 does not provide the media tothe total population 100 and is a trusted (e.g., neutral) third party(e.g., The Nielsen Company, LLC) for providing accurate media access(e.g., exposure) statistics. The AME 108 establishes a panel of users(e.g., the example sample population 102) who have agreed to providetheir demographic information and to have their media exposureactivities monitored. When an individual joins the sample population 102(e.g., a panel), the individual (e.g., panelist) provides detailedinformation concerning the person's identity and demographics (e.g.,gender, age, ethnicity, income, home location, occupation, etc.) to theAME 108.

The example panelist database 110 of the example AME 108 of FIG. 1stores and aggregates the example panelist data 104. The examplepanelist database 110 includes demographic data corresponding to eachpanelist in the example panel (e.g., the example sample population 102).Additionally, the example panelist database 110 tracks the mediaexposure of the panelists. For example, the panelist database 110 maystore indications related to media exposures for each panelist atvarious points in time. In such an example, the stored panelist data inthe example panelist database 110 may be used to determine that a firstpanelist was exposed to (A) a first media at a first and third time and(B) a second media at the first time and a second time. Additionally,the panelist database 110 may store indications of active and/orinactive panelists. For example, if a panelist is inactive, the panelistdatabase 110 may store an inactive indication for the panelist alongwith the time period in which the panelist is inactive. In this manner,the example weighter 112 can weigh the other panelists based on activepanelists (e.g., to better represent the example total population 100).

The example weighter 112 receives the example population data 106 andthe panelist data from the example panelist database 110 and generatesweights for panelists so that the panelist accurately represents theexample total population 100. In some examples, the weighter 112receives reach report settings from the example reach determiner 114 andgenerates the weights for the panelists at different points in timebased on the reach report settings. For example, if the reach reportsettings correspond to a reach report of reach of a television channelat three points in time for female panelists. The example weighter 112determines the appropriate weights for the female panelists from theexample panelist database 110 at the three points in time so that, ateach point in time, the female panelists accurately represent the totalpopulation of female users.

The example reach determiner 114 generates the example reach report 116based on panelists with time-dependent weights. The example reach report116 includes a reach of media at different points in time. As describedabove, the reach is an estimate of the cumulative total unique audienceat various points in time (e.g., the various points in timecorresponding to different sets of weights). In some examples, theexample reach determiner 114 includes a user interface to receive reachreport settings. The reach report settings customize the example reachreport 116 based on the desired points in time, the desired media, and adesired subset of the panelists analyzed. For example, the reach report116 may identify the reach of all panelists for a television show (e.g.,the Walking Dead) based on a first, second, and third time. In such anexample, the reach determiner 114 gathers panelist data stored in theexample panelist database 110 to identify which panelists were exposedto the Walking Dead at the first, second, and/or third times.Additionally, the example reach determiner 114 gathers the weights ofthe panelists at the first, second, and third times from the exampleweighter 112. The example reach determiner 114 generates the examplereach report 116 by determining the reach and/or the unique audience ateach of the three times based on the panelist data and the weights, asfurther described in conjunction with FIGS. 2 and 3.

FIG. 2 is a block diagram of the example reach determiner 114 of FIG. 1,disclosed herein, to generate the example reach report 116 bydetermining the reach of media with time dependent weights. The examplereach determiner 114 includes an example user interface 200, an exampleweight applicator 202, an example panelist database interface 204, anexample weighter interface 206, an example total audience calculator208, an example reach calculator 210, and an example report generator212.

The example user interface 200 interfaces with a user to receive thereach settings (e.g., the parameters for the example reach report 116).Because the reach is a cumulative unique audience for media, the reachsettings include various times which correspond to the desired reach.For example, a user may desire a cumulative reach for media at each daywithin a week. In such an example, the reach corresponds to thecumulative unique audience for the media during each day of the entireweek. In this manner, a panelist who is exposed to the media formultiple days counts toward the reach without overlap. Thus, the reachrepresents all the users that were exposed to the media within the weekperiod.

The example weight applicator 202 gathers panelist data from the examplepanelist database 110 via the example panelist database interface 204based on the reach settings received by the example user interface 200(e.g., including but not limited to data related to exposure to themedia identified in the reach settings). Additionally, the exampleweight applicator 202 gathers weights from the example weighter 112 viathe example weighter interface 206 corresponding to the panelists at thepoints in time identified in the reach settings. In some examples, thepanelist database interface 204 and the example weighter interface 206is the same interface. Additionally, the example weight applicator 202applies the gathered weights to the example panelists at the points intime identified in the reach settings.

The example total audience calculator 208 calculates a total audiencefor media at one or more points in time by determining weightedexposures to the media based on the weighted panelists exposed to themedia. In some examples, the total audience calculator 208 computes aweighted exposure matrix (e.g., the example weighted exposure matrix 408of FIG. 4) including all the weighted exposures of the panelists at theone or more points in time. The example total audience calculator 208generates the weighted exposures by applying the time dependent weightsto the panelists. In some examples, the total audience calculator 208applies a ‘1’ to a panelist who was exposed to the media at a point intime identified by the reach settings and a ‘0’ to a panelist who wasnot exposed to the media at a point in time identified by the reachsettings, where the ‘1’ and the ‘0’ are indicators (e.g., indicatingwhether the panelist was exposed to the media at the time). In suchexamples, the total audience calculator 208 applies (e.g., multiplies)the weights by the indicators to generate the weighted exposures.Alternatively, the example total audience calculator 208 may determinethe weighted exposures for the media at the one or more points in timeby only apply the weights to the subsets of panelists who were exposedto the media at the one or more points in time. In this manner, theexample total audience calculator 208 only applies the weights to thesubset of panelists that are exposed to the media. In some examples, theexample total audience calculator 208 identifies a weighted exposuretotal (e.g., representative of the total audience exposed to the media)for each of the one or more points in time by summing the weightedexposures of each panelist for a given point in time.

The example reach calculator 210 calculates the cumulative reach forcumulative points in time based on the weighted exposures calculated bythe example total audience calculator 208 and the reach settings. Theexample reach calculator 210 determines the largest (e.g., numerically)weighted exposure at the points in time for each panelist within thecumulative times, thereby generating cumulative weighted exposures foreach panelist. For example, for an hourly cumulative reach for mediaduring a 24 hour period, a first panelist may have been exposed to themedia at only the 1^(st) and 23^(rd) hour, where the weight for thefirst panelist at the 1^(st) hour is 15 and the weight for the 23^(rd)hour is 145, the example reach calculator 210 determines that thecumulative weighted exposure for the first panelist to be 145 (e.g., Max(15, 145), where max(a,b) outputs the maximum value between a and b). Ifa second panelist was exposed to the media at the 2^(nd), 3^(rd),10^(th), and 20^(th) hour, where the corresponding weights are 150, 10,132, and 75, the example reach calculator 210 determines that thecumulative weighted exposure for the second panelist to be 150 (e.g.,Max (150, 10, 132, 75)) during the 24-hour period. Alternatively, thereach may be calculated based on any time period or subset of times(e.g., a daily reach in a week period, a 3^(rd), 4^(th), and 20^(th)hour reach of a 24-hour period, etc.). If a third panelist is notexposed to the media at any point within the 24-hour period, the examplereach calculator 210 determines the cumulative weighted exposure to be0. If a fourth panelist is only exposed to the media at the 5^(th) hour,the example reach calculator 210 determines that the cumulative weightedexposure to be whatever weight is applied at the 5^(th) hour (e.g., 87,for example).

Once the cumulative weighted exposures are determined for each panelistbased on the reach settings, the example reach calculator 210 of FIG. 2identifies the reach of the media by summing the cumulative weightedtime of each panelist. Using the above example, the example reachcalculator 210 determines the reach to be 382 (e.g., 145 for the firstpanelist+150 for the second panelist+0 for the third panelist+87 for thefourth panelist=382). In some examples, the sum of the cumulativeweighted exposures may be more than the weight total (e.g.,representative of the universe, which is based on the sum of all theweights at each point in time) of the panelists. The reach cannot belarger than the universe of users. Accordingly, in such examples, thereach calculator 210 determines the reach to be the weight total. Insome examples, the reach calculator 210 determines the reach and adjuststhe reach to satisfy the universe totals (e.g., the sum of the weights).An example of a calculation of the reach is described in conjunctionwith FIG. 3. Once the example reach calculator 210 calculates the reach,the example report generator 212 generates the example reach report 116.The example report generator 212 may include any additional data relatedto the reach as defined by the reach settings. For example, the reachreport 116 may include demographics corresponding to the reach based onthe demographics of the panelist exposure to the media.

While example manners of implementing the example reach determiner 114of FIG. 1 are illustrated in FIG. 2, elements, processes and/or devicesillustrated in FIG. 2 may be combined, divided, re-arranged, omitted,eliminated and/or implemented in any other way. Further, the exampleuser interface 200, the example weight applicator 202, the examplepanelist database interface 204, the example weighter interface 206, theexample total audience calculator 208, the example reach calculator 210,the example report generator 212, and/or, more generally, the examplereach determiner 114 of FIG. 2 may be implemented by hardware, machinereadable instructions, software, firmware and/or any combination ofhardware, machine readable instructions, software and/or firmware. Thus,for example, any of the example user interface 200, the example weightapplicator 202, the example panelist database interface 204, the exampleweighter interface 206, the example total audience calculator 208, theexample reach calculator 210, the example report generator 212, and/or,more generally, the example reach determiner 114 of FIG. 2 could beimplemented by analog and/or digital circuit(s), logic circuit(s),programmable processor(s), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example userinterface 200, the example weight applicator 202, the example panelistdatabase interface 204, the example weighter interface 206, the exampletotal audience calculator 208, the example reach calculator 210, theexample report generator 212, and/or, more generally, the example reachdeterminer 114 of FIG. 2 is/are hereby expressly defined to include atangible computer readable storage device or storage disk such as amemory, a digital versatile disk (DVD), a compact disk (CD), a Blu-raydisk, etc. storing the software and/or firmware. Further still, theexample reach determiner 114 of FIG. 2 include elements, processesand/or devices in addition to, or instead of, those illustrated in FIG.3, and/or may include more than one of any or all of the illustratedelements, processes and devices.

Flowcharts representative of example machine readable instructions forimplementing the example reach determiner 114 of FIG. 2 are shown inFIG. 3. In the examples, the machine readable instructions comprise aprogram for execution by a processor such as the processor 512 shown inthe example processor platform 500 discussed below in connection withFIG. 5. The program may be embodied in machine readable instructionsstored on a tangible computer readable storage medium such as a CD-ROM,a floppy disk, a hard drive, a digital versatile disk (DVD), a Blu-raydisk, or a memory associated with the processor 512, but the entireprogram and/or parts thereof could alternatively be executed by a deviceother than the processor 512 and/or embodied in firmware or dedicatedhardware. Further, although the example program is described withreference to the flowchart illustrated in FIG. 3, many other methods ofimplementing the example reach determiner 114 of FIG. 2 mayalternatively be used. For example, the order of execution of the blocksmay be changed, and/or some of the blocks described may be changed,eliminated, or combined.

As mentioned above, the example process of FIG. 3 may be implementedusing coded instructions (e.g., computer and/or machine readableinstructions) stored on a tangible computer readable storage medium suchas a hard disk drive, a flash memory, a read-only memory (ROM), acompact disk (CD), a digital versatile disk (DVD), a cache, arandom-access memory (RAM) and/or any other storage device or storagedisk in which information is stored for any duration (e.g., for extendedtime periods, permanently, for brief instances, for temporarilybuffering, and/or for caching of the information). As used herein, theterm tangible computer readable storage medium is expressly defined toinclude any type of computer readable storage device and/or storage diskand to exclude propagating signals and to exclude transmission media. Asused herein, “tangible computer readable storage medium” and “tangiblemachine readable storage medium” are used interchangeably. Additionallyor alternatively, the example process of FIG. 3 may be implemented usingcoded instructions (e.g., computer and/or machine readable instructions)stored on a non-transitory computer and/or machine readable medium suchas a hard disk drive, a flash memory, a read-only memory, a compactdisk, a digital versatile disk, a cache, a random-access memory and/orany other storage device or storage disk in which information is storedfor any duration (e.g., for extended time periods, permanently, forbrief instances, for temporarily buffering, and/or for caching of theinformation). As used herein, the term non-transitory computer readablemedium is expressly defined to include any type of computer readablestorage device and/or storage disk and to exclude propagating signalsand to exclude transmission media. As used herein, when the phrase “atleast” is used as the transition term in a preamble of a claim, it isopen-ended in the same manner as the term “comprising” is open ended.

The example machine readable instructions illustrated in FIG. 3 may beexecuted to cause the reach determiner 114 of FIG. 2 to determine reachwith time dependent weights. Although the flowchart of FIG. 3 depictsexample steps in a given order, these steps are not exhaustive, variouschanges and modifications may be affected by one skilled in the artwithin the spirit and scope of the disclosure. For example, blocksillustrated in the flowchart may be performed in an alternative order ormay be performed in parallel.

FIG. 3 is an example flowchart 300 representative of example machinereadable instructions that may be executed to implement the reachdeterminer 114 of FIG. 2 to reach of media with time dependent weights.The example flowchart 300 of FIG. 3 is described in conjunction with theexample data 400 of FIG. 4. The example data 400 includes an exampleindicator matrix 402, an example time dependent weight matrix 404,example weight totals 406, an example weighted exposure matrix 408,example weighted exposure totals 410, an example cumulative weightedexposure matrix 412, example cumulative times 414 a-d, examplecumulative weighted exposure totals 416, and example reach 418. Theexample data 400 is based on exposure to media (e.g., a televisionprogram) at four different times for a panel of five panelists.Alternatively, reach may be calculated based on any number of panelistsat any number of times. Although the example data 400 of FIG. 4 isorganized in matrices, the example data 400 can be organized in anymanner.

At block 302, the example weight applicator 202 determines reach reportsettings based on received instructions (e.g., received by the exampleuser interface 200). As described above, the reach report settingsidentify the parameters for generating the example reach report 116 ofFIGS. 1 and 2. In the illustrated example of FIG. 4, the reach reportincludes a cumulative reach at a first time (t1), a second time (t2), athird time (t3), and a fourth time (t4). Alternatively, the reach reportsettings could include a cumulative reach at any number of times (e.g.,t1 and t2; t1, t3, and t4; etc.).

At block 304, the example total audience calculator 208 determines afirst subset of panelists exposed to the media (e.g., the televisionprogram) at a first time (t1). The example total audience calculator 208receives the exposure data via the example panelist database interface204. As illustrated in the example indicator matrix 402, panelistAndreas is included in the first subset of panelists exposed to themedia at t1 (e.g., represented by the value ‘1’). At block 306, theexample total audience calculator 208 determines an additional (e.g.,second) subset of panelists exposed to the media at an additional time(e.g., t2). As illustrated in the example indicator matrix 402,panelists Andreas, Dolores, Lloyd, and Marry are included in the secondsubset of panelists exposed to the media at time t2.

At block 308, the example total audience calculator 208 determines ifthere is an additional time to be analyzed based on the reach reportsettings. If the example total audience calculator 208 determines thatthere is an additional time to be analyzed (block 308: YES), the exampletotal audience calculator 208 continues to determine additional subsetsat the additional times until the times corresponding to the reachreport settings have all been analyzed. For example, in the illustratedexample of FIG. 4, the reach report settings correspond to a reachreport of the media for four times. Accordingly, the example totalaudience calculator determines a third subset of panelists exposed tothe media at time t3 (e.g., panelists Andreas, Dolores, and Lloyd) and afourth subset of panelists exposed to the media at time t4 (e.g.,panelists Andreas, Dolores, Marry, and Wiley).

If the example total audience calculator 208 determines that there isnot an additional time to be analyzed (block 308: NO), the exampleweight applicator 202 applies weights (e.g., time dependent weights) tothe N (e.g., 4) subsets to generate weighted exposures (block 310). Inthe illustrated example of FIG. 4, the total audience calculator 208applies the example indicator matrix 402 to the example time dependentweight matrix (e.g., by performing an element wise multiplication) togenerate the example weighted exposure matrix 408. Alternatively, theexample total audience calculator 208 may apply the correspondingweights (e.g., corresponding to the example time dependent weight matrix404) to the subsets (e.g., without applying the weights to panelists whohave not been exposed to the media, defined by the ‘0’ values). Forexample, the example total audience calculator 208 may apply the ‘26’weight to Andreas for the time t1 subset, the ‘19’ weight to Andreas,the ‘124’ weight to Dolores, the ‘175’ weight to Lloyd, and the ‘181’weight to Marry for the t2 subset, etc. In some examples, the totalaudience calculator 208 determines the total audience for the media ateach time by computing the example weighted exposure totals 410 at eachtime. The example total audience calculator 208 computes the weightedexposure totals 410 by summing the weighted exposures across allpanelists exposed to the media at the identified time. For example, theweighted exposure total 410 (e.g., the total audience) at time t3 is 402(e.g., 83+106+213).

At block 312, the example reach calculator 210 determines cumulativeweighted exposures based on the largest weighted exposure of eachpanelist at the cumulative times (e.g., t1, t2, t3, and t4) based on thereach report settings. In some examples, such as when the panelist isonly in one subset (e.g., Wiley), the largest weighted exposure for thepanelist at the cumulative times is the only applied weight (e.g., 343).In some examples, such as when the panelist is in multiple subsets, thelargest weighted exposure for the panelist is the largest applied weightat any of the times (e.g., t1, t2, t3, and t4) identified in the reachreport settings. If a panelist is not in any subset (e.g., was notexposed to the media at any of times identified in the reach reportsettings), the example reach calculator 210 applies a ‘0’ or doesn'tapply any data.

In the illustrated example of FIG. 4, the example reach calculator 210generates the cumulative weighted exposure matrix 412 based on arecursive model that looks at the previously applied weights for eachpanelist to identify the largest applied weight at different cumulativetimes 414 a-d. For example, looking at cumulative weights for panelistAndreas, the first cumulative time 414 a is not cumulative with anyother time (e.g., only included time t1). Accordingly, the example reachcalculator 210 determines that the weighted exposure applied to Andreasat time t1 (e.g., ‘26’) is the cumulative weighted exposure (e.g.,‘26’). At the second cumulative time 414 b, the example reach calculator210 determines that the cumulative weight exposure for times t1 and t2is 26 (e.g., Max (26, 19), where Max (a,b) outputs the maximum valuebetween a and b, 26 is the weight applied at time t1 and 19 is theweight applied at time t2), at the third cumulative time 414 c, theexample reach calculator 210 determines that the cumulative weightexposure for times t1, t2, and t3 is 83 (e.g., Max (26, 19, 83) or Max(26, 83), where 26 is maximum weight applied between t1 and t2 (e.g.,Max (26,19)) and 83 is the weight applied at time t3), etc.

At block 314, the example reach calculator 210 determines if thecumulative weighted exposure total at the cumulative time (e.g., one ofthe example cumulative weighted exposure totals 416) is larger than thelargest weight total at any of the times corresponding to the cumulativetime (e.g., any one of the example weight totals 406). The example reachcalculator 210 determines the cumulative weighted exposure total at thecumulative time by summing the cumulative weighted exposures at thecumulative time. For example, the example cumulative weighed exposuretotal 416 for the example “t1, t2, t3, and t4” cumulative time 414 d is1,087 (e.g., 134+141+213+256+343) and the largest of the example weighttotals 406 is 1,030 (e.g., Max (1000, 1010, 1020, 1030)). Accordingly,the cumulative weighted exposure total 416 for the example cumulativetime 414 d is larger than the largest of the example weight totals 406.The example reach 418 cannot be larger than the universe of users.Accordingly, the cumulative weighted exposure total corresponding to Ntimes cannot be larger than the largest universe total of the N times.

If the example reach calculator 210 determines that the cumulativeweighted exposure total at the cumulative time is larger than thelargest weight total at any of the times corresponding to the cumulativetime (block 316: YES), the example reach calculator 210 determines theexample reach 418 based on the largest weight total (block 316). Forexample, for the reach corresponding to time t1, t2, t3, and t4, theexample reach calculator 210 determines the example reach 418 to be1,030, because the example cumulative weighted exposure total of thet1-t4 cumulative time 414 d is 1,087 which is larger than the largestweight total of 1,030. Alternatively, the example reach calculator 210may calculate the reach to be 1,087 and adjust (e.g., reduce) the reachso that the reach is less than or equal to the largest weight total of1,030.

If the example reach calculator 210 determines that the cumulativeweighted exposure total at the cumulative time is not larger than thelargest weight total at any of the times corresponding to the cumulativetime (block 316: NO), the example reach calculator 210 determines theexample reach 418 based on the cumulative weighted exposure total (block318). For example, for the example reach 418 corresponding to time t1,t2, and t3, the example reach calculator 210 determines example thereach 418 to be 601, because the example cumulative weighted exposuretotal of the t1-t3 cumulative time 414 c is 601 (e.g., 83+124+213+181)which is not larger than the largest weight total of 1,020 (e.g., Max(1000, 1010, 1020)). At block 320, the example report generator 212generates the example reach report 116 based on the determined examplereach 418.

FIG. 5 is a block diagram of an example processor platform 500 capableof executing the instructions of FIG. 3 to implement the example memorycontroller 202 of FIG. 2. The processor platform 500 can be, forexample, a server, a personal computer, a mobile device (e.g., a cellphone, a smart phone, a tablet such as an iPad™), a personal digitalassistant (PDA), an Internet appliance, or any other type of computingdevice.

The processor platform 500 of the illustrated example includes aprocessor 512. The processor 512 of the illustrated example is hardware.For example, the processor 512 can be implemented by integratedcircuits, logic circuits, microprocessors or controllers from anydesired family or manufacturer.

The processor 512 of the illustrated example includes the example memory513 (e.g., a cache). The example processor 512 of FIG. 5 executes theinstructions of FIG. 3 to implement the example user interface 200, theexample weight applicator 202, the example panelist database interface204, the example weighter interface 206, the example total audiencecalculator 208, the example reach calculator 210, and the example reportgenerator 212 of FIG. 2 to implement the example reach determiner 114.The processor 512 of the illustrated example is in communication with amain memory including a volatile memory 514 and a non-volatile memory516 via a bus 518. The volatile memory 514 may be implemented bySynchronous Dynamic Random Access Memory (SDRAM), Dynamic Random AccessMemory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM) and/or anyother type of random access memory device. The non-volatile memory 516may be implemented by flash memory and/or any other desired type ofmemory device. Access to the main memory 514, 516 is controlled by amemory controller.

The processor platform 500 of the illustrated example also includes aninterface circuit 520. The interface circuit 520 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), and/or a PCI express interface.

In the illustrated example, one or more input devices 522 are connectedto the interface circuit 520. The input device(s) 522 permit(s) a userto enter data and commands into the processor 512. The input device(s)can be implemented by, for example, a sensor, a microphone, a camera(still or video), a keyboard, a button, a mouse, a touchscreen, atrack-pad, a trackball, isopoint and/or a voice recognition system.

One or more output devices 524 are also connected to the interfacecircuit 520 of the illustrated example. The output devices 524 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay, a cathode ray tube display (CRT), a touchscreen, a tactileoutput device, and/or speakers). The interface circuit 520 of theillustrated example, thus, typically includes a graphics driver card, agraphics driver chip or a graphics driver processor.

The interface circuit 520 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem and/or network interface card to facilitate exchange of data withexternal machines (e.g., computing devices of any kind) via a network526 (e.g., an Ethernet connection, a digital subscriber line (DSL), atelephone line, coaxial cable, a cellular telephone system, etc.).

The processor platform 500 of the illustrated example also includes oneor more mass storage devices 528 for storing software and/or data.Examples of such mass storage devices 528 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, RAIDsystems, and digital versatile disk (DVD) drives.

The coded instructions 532 of FIG. 3 may be stored in the mass storagedevice 528, in the volatile memory 514, in the non-volatile memory 516,and/or on a removable tangible computer readable storage medium such asa CD or DVD.

From the foregoing, it would be appreciated that the above disclosedmethods, apparatus, and articles of manufacture determine reach withtime dependent weights. Panels are constantly changing to includeadditional panelists or remove panelists. Additionally, panels changedue to panelist inactivity and/or meter equipment malfunction.Accordingly, weights applied to a panel at one point in time toaccurately correspond to a universe of users may be inaccurate at asecond point in time. Thus, weights are updated at different points intime so that weighting the panel accurately corresponds to the universeof users. However, when the weights change (e.g., become timedependent), conventional techniques of determining reach based on apanel become obsolete, as such conventional techniques depend on weightsbeing constant. Examples disclosed herein accurately determine reach ofmedia for different weights at different times. Accordingly, examplesdisclosed herein more accurately determine reach with time dependentweights then conventional methods.

Although certain example methods, apparatus and articles of manufacturehave been described herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

1. (canceled)
 2. An apparatus comprising: at least one memory;instructions; and processor circuitry to execute the instructions to:generate first weighted exposures based on a first plurality of weightsand a first plurality of exposures of a first audience to media at afirst time; generate second weighted exposures based on a secondplurality of weights and a second plurality of exposures of a secondaudience to the media at a second time different than the first time;determine a first cumulative weighted exposure based on a first valuecorresponding to a larger one of (a) a first one of the first weightedexposures corresponding to a first audience member and the first timeand (b) a first one of the second weighted exposures corresponding tothe first audience member and the second time, the first audience memberin both the first and second audiences; determine a second cumulativeweighted exposure based on a second value corresponding to a larger oneof (a) a second one of the first weighted exposures corresponding to asecond audience member and the first time and (b) a second one of thesecond weighted exposures corresponding to the second audience memberand the second time, the second audience member in both the first andsecond audiences; and combine the first and second cumulative weightedexposures to determine an unduplicated number of audience membersexposed to the media for the first and second times.
 3. The apparatus ofclaim 2, wherein: the first plurality of weights includes a first weightfor the first person and a second weight for the second person, thefirst plurality of weights corresponding to a total population at thefirst time; and the second plurality of weights includes a third weightfor the first person and a fourth weight for the second person, thesecond plurality of weights corresponding to the total population at thesecond time.
 4. The apparatus of claim 3, wherein the first plurality ofweights are time-dependent weights corresponding to whether the firstaudience was exposed to the media at the first time.
 5. The apparatus ofclaim 2, wherein the processor circuitry is to: sum the first weightedexposures to determine a first unique audience total corresponding tothe first time; and sum the second weighted exposures to determine asecond unique audience total corresponding to the second time.
 6. Theapparatus of claim 2, wherein the processor circuitry is to set a thirdcumulative weighted exposure to zero, the third cumulative weightedexposure for a third person not in either of the first audience or thesecond audience.
 7. The apparatus of claim 2, wherein the processorcircuitry is to sum the first cumulative weighted exposure and thesecond cumulative weighted exposure to combine the first and secondcumulative weighted exposures.
 8. The apparatus of claim 2, wherein theprocessor circuitry is to: sum the first plurality of weights todetermine a first total audience corresponding to the first time; andsum the second plurality of weights to determine a second total audiencecorresponding to the second time.
 9. The apparatus of claim 8, whereinwhen the unduplicated number of people is more than at least one of thefirst total audience or the second total audience, the processorcircuitry is to adjust the unduplicated number of people to be less thanor equal to the at least one of the first total audience or the secondtotal audience.
 10. An apparatus comprising: means for generatingweighted exposures, the means for generating the weighted exposures to:generate first weighted exposures based on a first plurality of weightsand a first plurality of exposures of a first audience to media at afirst time; and generate second weighted exposures based on a secondplurality of weights and a second plurality of exposures of a secondaudience to the media at a second time different than the first time;means for determining cumulative weighted exposures, the means fordetermining the cumulative weighted exposures to: determine a firstcumulative weighted exposure based on a first value corresponding to alarger one of (a) a first one of the first weighted exposurescorresponding to a first audience member and the first time and (b) afirst one of the second weighted exposures corresponding to the firstaudience member and the second time, the first audience member in boththe first and second audiences; and determine a second cumulativeweighted exposure based on a second value corresponding to a larger oneof (a) a second one of the first weighted exposures corresponding to asecond audience member and the first time and (b) a second one of thesecond weighted exposures corresponding to the second audience memberand the second time, the second audience member in both the first andsecond audiences; and means for combining the first and secondcumulative weighted exposures to determine an unduplicated number ofpeople exposed to the media for the first and second times.
 11. Theapparatus of claim 10, wherein: the first plurality of weights includesa first weight for the first person and a second weight for the secondperson, the first plurality of weights corresponding to a totalpopulation at the first time; and the second plurality of weightsincludes a third weight for the first person and a fourth weight for thesecond person, the second plurality of weights corresponding to thetotal population at the second time.
 12. The apparatus of claim 11,wherein the first plurality of weights are time-dependent weightscorresponding to whether the first audience was exposed to the media atthe first time.
 13. The apparatus of claim 10, wherein the means fordetermining the cumulative weighted exposures is to: sum the firstweighted exposures to determine a first unique audience totalcorresponding to the first time; and sum the second weighted exposuresto determine a second unique audience total corresponding to the secondtime.
 14. The apparatus of claim 10, wherein the means for determiningthe cumulative weighted exposures is to set a third cumulative weightedexposure to zero, the third cumulative weighted exposure for a thirdperson not in either of the first audience or the second audience. 15.The apparatus of claim 10, wherein the means for combining the first andsecond cumulative weighted exposures is to sum the first cumulativeweighted exposure and the second cumulative weighted exposure to combinethe first and second cumulative weighted exposures.
 16. The apparatus ofclaim 10, wherein the means for determining the cumulative weightedexposures is to: sum the first plurality of weights to determine a firsttotal audience corresponding to the first time; and sum the secondplurality of weights to determine a second total corresponding to at thesecond time.
 17. The apparatus of claim 16, wherein when theunduplicated number of people is more than at least one of the firsttotal audience or the second total audience, the means for combining thefirst and second cumulative weighted exposures is to adjust theunduplicated number of people to be less than or equal to the at leastone of the first total audience or the second total audience.
 18. Atleast one non-transitory computer readable medium comprisinginstructions that, when executed, cause one or more processors to atleast: generate first weighted exposures based on a first plurality ofweights and a first plurality of exposures of a first audience to mediaat a first time; generate second weighted exposures based on a secondplurality of weights and a second plurality of exposures of a secondaudience to the media at a second time different than the first time;determine a first cumulative weighted exposure based on a first valuecorresponding to a larger one of (a) a first one of the first weightedexposures corresponding to a first audience member and the first timeand (b) a first one of the second weighted exposures corresponding tothe first audience member and the second time, the first audience memberin both the first and second audiences; determine a second cumulativeweighted exposure based on a second value corresponding to a larger oneof (a) a second one of the first weighted exposures corresponding to asecond audience member and the first time and (b) a second one of thesecond weighted exposures corresponding to the second audience memberand the second time, the second audience member in both the first andsecond audiences; and combine the first and second cumulative weightedexposures to determine an unduplicated number of audience membersexposed to the media for the first and second times.
 19. The at leastone non-transitory computer readable medium of claim 18, wherein: thefirst plurality of weights includes a first weight for the first personand a second weight for the second person, the first plurality ofweights corresponding to a total population at the first time; and thesecond plurality of weights includes a third weight for the first personand a fourth weight for the second person, the second plurality ofweights corresponding to the total population at the second time. 20.The at least one non-transitory computer readable medium of claim 19,wherein the first plurality of weights are time-dependent weightscorresponding to whether the first audience was exposed to the media atthe first time.
 21. The at least one non-transitory computer readablemedium of claim 18, wherein the instructions cause the one or moreprocessors to: sum the first weighted exposures to determine a firstunique audience total corresponding to the first time; and sum thesecond weighted exposures to determine a second unique audience totalcorresponding to the second time.